Background

Current diagnostic criteria of HIV-associated neurocognitive disorders (HAND) rely on neuropsychological assessments. The aim of this study was to evaluate if gray matter volumes (GMV) can distinguish people with HAND, neurocognitively unimpaired people with HIV (unimpaired PWH), and uninfected controls using linear discriminant analyses.

Methods

A total of 231 participants, including 110 PWH and 121 uninfected controls, completed a neuropsychological assessment and an MRI protocol. Among PWH, HAND (n = 48) and unimpaired PWH (n = 62) designations were determined using the widely accepted Frascati criteria. We then assessed the extent to which GMV, corrected for intracranial volume, could accurately distinguish the three groups using linear discriminant analysis. Sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, area under the curve (AUC), and accuracy were computed for each model using the classification results based on GMV compared to the neuropsychological assessment.

Results

The best performing model was comprised of bilaterally combined GMV and was stratified by sex. Among males, sensitivity was 85.2% (95% CI: 66.3%–95.8%), specificity was 97.0% (95% CI: 91.6%-99.4%), and the AUC was 0.91 (95% CI: 0.83–0.99). Among females, sensitivity was 100.0% (95% CI: 83.9%–100.0%), specificity was 98.8% (95% CI: 93.4%-100.0%), and the AUC was 0.99 (95% CI: 0.98–1.00).

Conclusions

GMV accurately discriminated HAND from unimpaired PWH and controls. Measures of GMV may be highly sensitive to HAND, and revisions to the Frascati criteria should consider including GMV in conjunction with a neuropsychological assessment to diagnose HAND.

中文翻译：

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灰质体积可区分认知受损和未受损的艾滋病毒感染者

 背景

目前 HIV 相关神经认知障碍 (HAND) 的诊断标准依赖于神经心理学评估。本研究的目的是使用线性判别分析来评估灰质体积 (GMV) 是否可以区分 HAND 患者、神经认知未受损的 HIV 感染者（未受损的 PWH）和未感染的对照。

 方法

共有 231 名参与者（包括 110 名感染者和 121 名未感染对照者）完成了神经心理学评估和 MRI 方案。在 PWH 中，HAND ( n = 48) 和未受损 PWH ( n = 62) 的称号是使用广泛接受的弗拉斯卡蒂标准确定的。然后，我们使用线性判别分析评估了校正颅内体积的 GMV 能够准确地区分三组的程度。使用基于 GMV 的分类结果与神经心理学评估进行比较，计算每个模型的敏感性、特异性、阳性似然比、阴性似然比、曲线下面积 (AUC) 和准确性。

 结果

表现最佳的模型由双边组合 GMV 组成，并按性别分层。在男性中，敏感性为 85.2%（95% CI：66.3%–95.8%），特异性为 97.0%（95% CI：91.6%-99.4%），AUC 为 0.91（95% CI：0.83–0.99）。在女性中，敏感性为100.0%（95% CI：83.9%–100.0%），特异性为98.8%（95% CI：93.4%-100.0%），AUC为0.99（95% CI：0.98–1.00）。

 结论

GMV 准确地区分 HAND 与未受损的 PWH 和对照。 GMV 测量可能对 HAND 高度敏感，弗拉斯卡蒂标准的修订应考虑将 GMV 与神经心理学评估结合起来以诊断 HAND。